Advanced Measurement Systems to evaluate CSP Plants Robert Pitz-Paal DLR Institute of Solar Research > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 1
Advanced Measurement Systems to evaluate CSP Plants
Robert Pitz-Paal DLR Institute of Solar Research
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 1
• Challenges for measurements in CSP power plants
• Parabolic Trough Fields: • Airborne predictions of optical field performance • Hydrogen accumulation in parabolic trough receivers • Cloud shadow prediction in the solar field
• Solar Tower
• Optical quality of heliostat field and flux distribution on receiver • Air return ratio in open volumetric receiver systems
• Summary
Outline
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 2
• Challenges for measurements in CSP power plants
• Parabolic Trough Fields: • Airborne predictions of optical field performance • Hydrogen accumulation in parabolic trough receivers • Cloud shadow prediction in the solar field
• Solar Tower
• Optical quality of heliostat field and flux distribution on receiver • Air return ratio in open volumetric receiver systems
• Summary
Outline
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 3
Challenges for measurements in CSP power plants
• Measurement object extended or distributed over several square miles
• Limited access (e.g. tower)
• Measurement should not disturb operation
• Sensors preferably non invasive
• High measurement precision requirements
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 4
• Challenges for measurements in CSP power plants
• Parabolic Trough Fields: • Airborne predictions of optical field performance • Hydrogen accumulation in parabolic trough receivers • Cloud shadow prediction in the solar field
• Solar Tower
• Optical quality of heliostat field and flux distribution on receiver • Air return ratio in open volumetric receiver systems
• Summary
Outline
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 5
QFly – airborne prediction of the optical performance of parabolic trough collector fields
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 6
Failure Detection, Quality Control, Optimization
High resolution
Mirror shape HCE position
Survey
Mirror shape Alignment Torsion Tracking
Thermo
Defective HCEs Heat loss
50 MW PTC solar field (Andasol I) QFly UAV
X
Z
camera
dabs
dcam
∆z
∆x
reflector
f
nu
nl
∆αu
α1,u
αu
α1,l
∆αl
αl
2. Qualification of Concentrators Deflectometry
Slide 8 www.dlr.de/enerMENA
2. Qualification of Concentrators Deflectometry – Image Acquisition
QFly measurement principle
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 9
• Plan for Flight Route using GPS waypoints
• Aerial images showing absorber tube reflex
• Scaling/reference system for close-range photogrammetry
1
QFly measurement principle
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 10
• Calculation of camera positions relative to each collector via photogrammetry
• Artificial, coded and natural markers
• Accuracy of 3D coordinates ~ 5 mm
2
QFly measurement principle
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 11
• Calculation of lateral and vertical HCE deviation from focal line via photogrammetric approach
• Deviations Qfly to reference: • RMS dX < 2.0 mm
3
QFly measurement principle
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 12
• Calculation of slope deviations in curvature direction (SDx, in mrad) from absorber reflex, camera positions and absorber position
4
QFly measurement principle
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 13
• Intercept factor via ray-tracing based on measured geometry
• Includes blocking and shading effects
• Assumptions on other error sources
6
QFly measurement principle
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 14
Effort per collector (SCA) 150 m: 2 hours 0.5 hours 4 hours
Optical: • Comparison with reference data from
photogrammetry • Mirror:
• Difference of SDx RMS values < 0.4 mrad (due to limited spatial resolution of photogrammetry)
• Absorber tube position
RMS of differences: • < 2.0 mm horizontal • < 2.1 mm vertical
Validation
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 15
Thermal: • Comparison with thermal efficiency of
EuroTrough module on Kontas test-bench (PSA Almeria)
• Good agreement between : • via thermal measurement • via QFly measurement
optη
• Challenges for measurements in CSP power plants
• Parabolic Trough Fields: • Airborne predictions of optical field performance • Hydrogen accumulation in parabolic trough receivers • Cloud shadow prediction in the solar field
• Solar Tower
• Optical quality of heliostat field and flux distribution on receiver • Air return ratio in open volumetric receiver systems
• Summary
Outline
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 16
• Hydrogen accumulation would deteriorate vacuum insulation of receivers
• Counteractions against hydrogen in receiver (getter, barrier coating) designed for H2 limit concentration / pressure in heat transfer fluid (HTF)
• H2 monitoring and HTF processing focussed on H2 removal, required to keep H2 level below deterioration limit
Hydrogen accumulation in parabolic trough receivers: Effects and Counteractions
DLR.de • Chart 17
Getter Diffusion barrier
H2 limit
noble gas capsule
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
Thermal aging of HTF causes slow hydrogen formation
DLR.de • Chart 18
H
H
HH
H2
quaterphenyl(s)
benzene
terphenyl(s)hydrogen
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
Measurement of hydrogen in oil samples in solar field
DLR.de • Chart 19
2Hx
2
2
2
)(H
HTF
lHH H
nn
p =
2)(
22 H
npn HTFHlH =
Hydrogen in gas phase
RT
mVpn HTF
HTFgesH
gH
)(2
2 )(ρ
−=
via GC 22 HgesH xpp =
)(2 lHn
)(2 gHn
HTF, hot HTF, cold
cooling )(2 gesHn
Hydrogen in liquid phase
• Sampling of liquid and gas phase with steel cylinders inline (pressurized & hot)
• Analysis of (all) dissolved gases offline (lab)
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
• Direct result of measurement: µmol/kg hydrogen in oil
• Receiver manufacturer’s hydrogen limit: e. g. 0.3 mbar
• Conversion from concentration to pressure via Henry coefficient (gas solubility, H, from gas dissolution experiments) pH2 = HH2(T) * xH2
Gas Content: Concentration vs. Pressure
DLR.de • Chart 20 > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
• Eutectic mixture of biphenyl (BP) and diphenyl oxide (DPO) forms hydrogen at increasing rate on prolonged operation
• New silicone fluids form less hydrogen on prolonged operation at elevated temperature
Hydrogen in Heat Transfer Fluid Reduced Formation using Silicone Fluids?
DLR.de • Chart 21 > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
• Challenges for measurements in CSP power plants
• Parabolic Trough Fields: • Airborne predictions of optical field performance • Hydrogen accumulation in parabolic trough receivers • Cloud shadow prediction in the solar field
• Solar Tower
• Optical quality of heliostat field and fux distribution on receiver • Air return ratio in open volumetric receiver systems
• Summary
Outline
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 22
DLR.de • Chart 23
Cloud shadow prediction in CSP Plants Optimize energetic and financial yield & plant life time • CSP plant operation involves decisions, e.g.
• selection of operation mode • tower plants: mirror focus control (avoid fast temperature changes of
receiver, avoid overload dumping with dynamic aim-point selection) • trough plants: individual heat transfer fluid mass flow in different parts of the
solar field
Andasol parabolic trough plants
Imag
e: A
ndas
ol
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
DLR.de • Chart 24
• Challenges: • High variability • Complex cloud formation/motion
• Captured at PSA
2014- 05-28, 10:00 - 17:00
Cloud Movement Analysis irradiance maps with high temporal and spatial resolution (nowcasts and live information) from cloud camera system
ground observation from camera on solar tower (90 m)
Whole Sky Imager (WSI)
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
DLR.de • Chart 25
Cloud height from LIDARs
Automatic solar trackers with pyrheliometer
pyranometers
+ Rotating Shadowband Irradiometers (inside PSA & 2km south)
100 m
Imag
e: G
oogl
e, C
IEM
AT, D
LR
Mobotix Q24
2 Mobotix Allround M25
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
Approach: Voxel carving
1. Cloud-segmentation
2. Back-projection of detected clouds view cone
3. Intersection of view cones = cloud
WSI 1 WSI 2
DLR.de • Chart 26 > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
Approach: Voxel carving
1. Cloud-segmentation
2. Back-projection of detected clouds view cone
3. Intersection of view cones = cloud
4. Calculation of modeled shadow
WSI 1 WSI 2
DLR.de • Chart 27 > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
Validation of modeled shadow
Reference Shadow cam
(Pixel) Shadow No Shadow
Mod
el
Voxe
l Car
v.
Shadow TP FP
No shadow FN TN
ACC = (TP + TN)/surface = 0.76
• Tested with ~100 cases with average ACC = 0,72
• Prototype of system (hardware + processing) running live at PSA
DLR.de • Chart 28 > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
• Challenges for measurements in CSP power plants
• Parabolic Trough Fields: • Airborne predictions of optical field performance • Hydrogen accumulation in parabolic trough receivers • Cloud shadow prediction in the solar field
• Solar Tower
• Optical quality of heliostat field and flux distribution on receiver • Air return ratio in open volumetric receiver systems
• Summary
Outline
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 29
Evaluation of Heliostat Field Optical Quality
Problem: Measurement of flux density distribution on aperture is not practical for large commercial (external) receivers
Solution: Measurement supported simulation = Assessment of field parameters by qualification of entire heliostat field (or random samples) as basis for flux density calculation through ray tracing, verified by direct measurements
slope component and system geometry
reflectivity sun
tracking attenuation
structural deformation
ray tracing simulation
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 30
Assessment of Heliostat Field Parameters parameter(s) assessment method coverage
slope (mirror shape and canting) automated deflectometry total/ sample
structural deformation on-site photogrammetry sample
component and system geometry (size and positions of heliostats and receiver)
triangulation, stereo camera sample
reflectance on-site reflectometer device sample
tracking accuracy calibration (camera/target) total
sun (DNI, sunshape) on-site pyrheliometer and CCD camera total
atmospheric attenuation transmissometer, scatterometer sample
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 31
Automated Deflectometry Measurement
Deflectometry (= fringe reflection): observation of deformation of regular stripe
patterns through reflection
Principle: • resolution: 106 points per heliostat • accuracy: < 0.2 mrad*
can be used for • prototype testing • qualification during production
*Ulmer, S. et al. Automated high resolution measurement
of heliostat slope errors. Sol. Energy (2010)
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 32
Automated deflectometry measurement of existing heliostat field (total/samples)
Automated Deflectometry Measurement
• automatic selection of single heliostats/groups
• automatic measurement and data processing
• output of report and input data file for ray tracing
• performance: ~60sec./hel.
can be used for: • field qualification during
commissioning • regular assessment of field
quality during operation
Jülich 2014/15
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 33
High Precision Ray-Tracing of Heliostat Field
• ray tracing using deflectometry surface data in original resolution
• efficient ray generation and usage; utilization of modern cpu capabilites (SIMD,
multi-threading) → calculation performance: > 60·106 rays/sec using a standard pc (8 cores) • successful validation by comparison with flux measurement*
Flux Measurement Simulation *Belhomme et al. A New Fast Ray Tracing Tool for High-Precision Simulation of Heliostat Fields ASME J. Sol. Energy Eng., (2009)
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 34
Measurement Supported Simulation of Heliostat Field
parameter assessment
calculation of flux distribution
support by spot meters
• high precision measurement systems
• calculation model covering all influence
parameters
• reliability (confidence) improved by • high sampling rate
• direct measurements
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 35
Application
Plant owner
1. During hot commissioning: Which component is not meeting the contracted specifications? 2. During commercial operation: Why do we perform below expectation? (… and what can we do to improve?)
• up to 100% measurement of guaranteed values • calculation of intercept power with certain confidence level • assessment of field and receiver efficiency requirement: agree on measurement method and simulation model during contract negotiations
• applicable to existing systems • continuous / repeated measurements • updated calculation every 15-60 minutes (for monitoring)
use gathered data to optimize aim point distribution on receiver surface (next slide)
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 36
Simulation-Based Aim Point Optimization
Example: improvement of Solar Tower Jülich field performance
Ray tracing simulations based on deflectometry measurement of random samples
original heliostats 6 aim points
intercept: 0.706
new heliostat facets same aim points intercept: 0.828
new heliostat facets aim point optimization
intercept: 0.861
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 37
• Challenges for measurements in CSP power plants
• Parabolic Trough Fields: • Airborne predictions of optical field performance • Hydrogen accumulation in parabolic trough receivers • Cloud shadow prediction in the solar field
• Solar Tower
• Optical quality of heliostat field and flux distribution on receiver • Air return ratio in open volumetric receiver systems
• Summary
Outline
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 38
Open volumetric air receiver
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 39
• Influences the total efficiency • Depends on environmental and
operational conditions • Can be improved has to be measured
Keyfactor air return ratio:
ARR =�̇�𝑚return�̇�𝑚out
Solar Tower Jülich > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 40
Difficult measurement environment: • High air mass flows • High surface temperatures • Concentrated solar radiation • Large scales Two approaches to measure ARR:
Quantitative ARR measurement with tracer gas
Qualitative ARR measurement with Induced Infrared
Thermography
Tracer Gas Measurement
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 41
• Helium is used as tracer gas • Helium is added to the system
• Statically • Dynamically
• The Helium concentration response 𝜒𝜒𝐻𝐻𝐻𝐻 is measured using a mass spectrometer
Static Tracer Gas Measurement
ARRstat = 𝜒𝜒𝐻𝐻𝐻𝐻,𝑖𝑖𝑖𝑖𝜒𝜒𝐻𝐻𝐻𝐻,𝑜𝑜𝑜𝑜𝑜𝑜
• Both measuring points needed • Straight forward measurement
ARRstat = 61.5 ± 2.5 %
Measurement at receiver model:
Tracer Gas Measurement
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 42
Dynamic Tracer Gas Measurement • Only one measuring point needed • ARR from dynamic response
𝜒𝜒𝐻𝐻𝐻𝐻,𝑙𝑙𝐻𝐻𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 𝑡𝑡 = 𝐴𝐴 1 − 𝐴𝐴𝐴𝐴𝐴𝐴𝑡𝑡\T 𝜒𝜒𝐻𝐻𝐻𝐻,𝑡𝑡𝑡𝑡𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙𝑙 𝑡𝑡 = 𝐴𝐴 ⋅ 𝐴𝐴𝐴𝐴𝐴𝐴𝑡𝑡\T
• Helium is used as tracer gas • Helium is added to the system
• Statically • Dynamically
• The Helium concentration response 𝜒𝜒𝐻𝐻𝐻𝐻 is measured using a mass spectrometer
ARRdyn = 63.2 ± 4.0 %
Measurement at receiver model:
Further measurements needed: • Circulation period T • Transfer function for dynamic error
correction using system identification
Induced Infrared Thermography (IIT) > Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 43
Front view Side view Filter
Tracer Gas 2
IR-Camera
• DLR has developed a variety of tools in order to perform measurements in commercial scale trough and tower systems that go far beyond simple heat balance measurements
• All measurements have been validated in large scale facilities like the Plataforma Solar de Almería or the Research Facility Solar Tower Jülich
• Some of the measurements have been applied already in commercial full scale power plants in cooperation with the DLR Spin-off company CSP Services
• Commercial CSP applications require new methods under commercial conditions DLR and partners have the tools and validations to provide solutions
In addition we have extensive laboratory testing facilities for industrial components ……
Summary and Conclusion
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015 DLR.de • Chart 44
Mirror Panels • Shape accuracy (also sag under different load conditions) • Reflectance (specular and spectral hemispheric) • Corrosion and abrasion tests • Outdoor exposure at desert and coastal sites
Parabolic Trough Receiver • Optical efficiency • Thermal power loss • Overheating & thermal cycling (aging of coating) • Bellow fatigue tests (mechanical aging) • Anti-reflective coating of glass envelope • Operability tests under real solar conditions Collectors • Peak efficiency, Thermal characteristics, Incident angle
modifier, behavior under different load conditions, Torsion
QUARZ Test and Qualification Center Performance and Durability Testing
DLR.de • Chart 45
Mirror shape measurement
Receiver optical performance test
Rotary collector test bench (KONTAS)
> Measurements in CSP Plants - ASME Power & Energy 2015 Keynote > Robert Pitz-Paal > July 1st, 2015
> DLR Solar Research > Dr. Eckhard Lüpfert > MASEN-KfW Rabat June 2015 > Confidential DLR.de • Chart 47
Thank you for your attention Contact: [email protected]